3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

3D-e-Chem : Structural Cheminformatics Workflows for Computer-Aided Drug Discovery. / Kooistra, Albert J.; Vass, Márton; McGuire, Ross; Leurs, Rob; de Esch, Iwan J.P.; Vriend, Gert; Verhoeven, Stefan; de Graaf, Chris.

In: ChemMedChem, Vol. 13, No. 6, 20.03.2018, p. 614-626.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Kooistra, AJ, Vass, M, McGuire, R, Leurs, R, de Esch, IJP, Vriend, G, Verhoeven, S & de Graaf, C 2018, '3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery', ChemMedChem, vol. 13, no. 6, pp. 614-626. https://doi.org/10.1002/cmdc.201700754

APA

Kooistra, A. J., Vass, M., McGuire, R., Leurs, R., de Esch, I. J. P., Vriend, G., ... de Graaf, C. (2018). 3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery. ChemMedChem, 13(6), 614-626. https://doi.org/10.1002/cmdc.201700754

Vancouver

Kooistra AJ, Vass M, McGuire R, Leurs R, de Esch IJP, Vriend G et al. 3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery. ChemMedChem. 2018 Mar 20;13(6):614-626. https://doi.org/10.1002/cmdc.201700754

Author

Kooistra, Albert J. ; Vass, Márton ; McGuire, Ross ; Leurs, Rob ; de Esch, Iwan J.P. ; Vriend, Gert ; Verhoeven, Stefan ; de Graaf, Chris. / 3D-e-Chem : Structural Cheminformatics Workflows for Computer-Aided Drug Discovery. In: ChemMedChem. 2018 ; Vol. 13, No. 6. pp. 614-626.

Bibtex

@article{df73c07aa9e24ffaaf2f2c0e3e6ca913,
title = "3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery",
abstract = "eScience technologies are needed to process the information available in many heterogeneous types of protein–ligand interaction data and to capture these data into models that enable the design of efficacious and safe medicines. Here we present scientific KNIME tools and workflows that enable the integration of chemical, pharmacological, and structural information for: i) structure-based bioactivity data mapping, ii) structure-based identification of scaffold replacement strategies for ligand design, iii) ligand-based target prediction, iv) protein sequence-based binding site identification and ligand repurposing, and v) structure-based pharmacophore comparison for ligand repurposing across protein families. The modular setup of the workflows and the use of well-established standards allows the re-use of these protocols and facilitates the design of customized computer-aided drug discovery workflows.",
keywords = "cheminformatics workflows, KNIME, ligand design, ligand repurposing, target prediction",
author = "Kooistra, {Albert J.} and M{\'a}rton Vass and Ross McGuire and Rob Leurs and {de Esch}, {Iwan J.P.} and Gert Vriend and Stefan Verhoeven and {de Graaf}, Chris",
year = "2018",
month = "3",
day = "20",
doi = "10.1002/cmdc.201700754",
language = "English",
volume = "13",
pages = "614--626",
journal = "ChemMedChem",
issn = "1860-7179",
publisher = "Wiley - V C H Verlag GmbH & Co. KGaA",
number = "6",

}

RIS

TY - JOUR

T1 - 3D-e-Chem

T2 - Structural Cheminformatics Workflows for Computer-Aided Drug Discovery

AU - Kooistra, Albert J.

AU - Vass, Márton

AU - McGuire, Ross

AU - Leurs, Rob

AU - de Esch, Iwan J.P.

AU - Vriend, Gert

AU - Verhoeven, Stefan

AU - de Graaf, Chris

PY - 2018/3/20

Y1 - 2018/3/20

N2 - eScience technologies are needed to process the information available in many heterogeneous types of protein–ligand interaction data and to capture these data into models that enable the design of efficacious and safe medicines. Here we present scientific KNIME tools and workflows that enable the integration of chemical, pharmacological, and structural information for: i) structure-based bioactivity data mapping, ii) structure-based identification of scaffold replacement strategies for ligand design, iii) ligand-based target prediction, iv) protein sequence-based binding site identification and ligand repurposing, and v) structure-based pharmacophore comparison for ligand repurposing across protein families. The modular setup of the workflows and the use of well-established standards allows the re-use of these protocols and facilitates the design of customized computer-aided drug discovery workflows.

AB - eScience technologies are needed to process the information available in many heterogeneous types of protein–ligand interaction data and to capture these data into models that enable the design of efficacious and safe medicines. Here we present scientific KNIME tools and workflows that enable the integration of chemical, pharmacological, and structural information for: i) structure-based bioactivity data mapping, ii) structure-based identification of scaffold replacement strategies for ligand design, iii) ligand-based target prediction, iv) protein sequence-based binding site identification and ligand repurposing, and v) structure-based pharmacophore comparison for ligand repurposing across protein families. The modular setup of the workflows and the use of well-established standards allows the re-use of these protocols and facilitates the design of customized computer-aided drug discovery workflows.

KW - cheminformatics workflows

KW - KNIME

KW - ligand design

KW - ligand repurposing

KW - target prediction

UR - http://www.scopus.com/inward/record.url?scp=85042062175&partnerID=8YFLogxK

U2 - 10.1002/cmdc.201700754

DO - 10.1002/cmdc.201700754

M3 - Journal article

VL - 13

SP - 614

EP - 626

JO - ChemMedChem

JF - ChemMedChem

SN - 1860-7179

IS - 6

ER -

ID: 199351335